Senior Business Intelligence Engineer, Private Pricing Programs and Experiences
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65 open data analyst jobs at 34 employers, updated twice a day.
As of 23 September, 65 data analyst roles are open at 34 employers. 2 new roles have been posted since 21 September. The countries with the most are the United States, India and Japan. Of the roles that say how they work, 15% are remote or hybrid.
Among the roles listed here, the United States accounts for roughly half the openings, with India making up about a fifth and Japan, Brazil, and Canada each contributing a small share. European postings are spread across Germany, the United Kingdom, Ireland, and Portugal. The majority of roles sit at senior or lead level, while junior and intern positions make up a small minority. Most openings have been posted within the past month, with a good portion arriving in the last week, suggesting a reasonably active and fresh pool. Hiring is concentrated, with around half of all roles sitting at just five employers. SQL and Python dominate skill mentions, and there are notable references to cloud platforms and, in roughly a fifth of descriptions, to large language models and AI agents.
Figures are measured every Monday.
A data analyst collects, cleans and explores datasets, identifies trends and patterns, and translates findings into dashboards, charts and written summaries for both technical and non-technical audiences. The role sits between a data engineer, who builds and maintains pipelines, and a data scientist, who tends to work on predictive modelling and research. In a business intelligence context, analysts query company data stores to produce recurring financial and market intelligence reports and keep dashboards up to date. Progression typically runs from associate or junior analyst through to senior and principal levels, with a managerial track also common. Entry routes include relevant degrees, vocational qualifications, and apprenticeships.
SQL appears in the large majority of descriptions, making it the clearest baseline expectation. Python follows closely, and statistical reasoning is mentioned in well over half. Cloud platforms, especially AWS, appear often enough to be worth demonstrating. A notable minority of descriptions mention large language models and AI agents, reflecting growing overlap with applied AI work. Spark and Snowflake appear in a smaller but meaningful share, pointing to data warehouse and big-data processing familiarity as a differentiator at more senior levels.
Share of the open roles' descriptions that mention it, from a sample of 65. A mention is not a requirement.
The strong majority of roles listed here specify on-site work, making fully office-based arrangements the clear norm for this role at present. Hybrid arrangements account for a small share, and fully remote positions are a small minority. Candidates who need flexible or location-independent work will find the options limited compared with some neighbouring technical roles.
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